A dependency-free (pure standard-library) Python tool that turns the streaming QoE metrics this article frames into an estimated engagement impact, using the published causal/empirical models so the output traces to a citable source. It does NOT decode video or compute picture metrics; it consumes the session-level numbers a player analytics stack already reports. (1) STARTUP -> ABANDONMENT: applies the Krishnan-Sitaraman (IMC 2012) finding — abandonment begins past ~2s and rises ~5.8 percentage
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The handbook · 7 volumes
Fora Soft Video Engineering Handbook
This Python calculator turns startup time, rebuffering and bitrate into an estimated engagement impact using published models. Our seven-volume handbook covers the levers behind each number: Volume 3 on ABR, CDNs, players and QoE monitoring, Volume 1 on encoding quality per bit, and Volume 6 on AI models that predict viewer response. Written by Nikolay Sapunov, CEO at Fora Soft.
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